Inferring the rules of social interaction in migrating caribou

Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada. Through a Bayesian analysis of trajectories we reveal the fine-scale interaction rules of migrating caribou and show they are attracted to one another and copy directional choices of neighbours, but do not interact through clearly defined metric or topological interaction ranges. By explicitly considering the role of social information on movement decisions we construct a map of near neighbour influence that quantifies the nature of information flow in these herds. These results will inform more realistic, mechanism-based models of migration in caribou and other social ungulates, leading to better predictions of spatial use patterns and responses to changing environmental conditions. Moreover, we anticipate that the protocol we developed here will be broadly applicable to study social behaviour in a wide range of migratory and non-migratory taxa. This article is part of the theme issue ‘Collective movement ecology’.

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Design and Evaluation of Sensor Housing for Boundary Layer Profiling Using Multirotors

Sensors ◽

10.3390/s19112481 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2481 ◽

Cited By ~ 5

Author(s):

Ashraful Islam ◽

Adam L. Houston ◽

Ajay Shankar ◽

Carrick Detweiler

Keyword(s):

Boundary Layer ◽

High Speed ◽

Ground Level ◽

Radiation Shielding ◽

Unmanned Aerial Systems ◽

Heat Sources ◽

Wide Range ◽

Artificial Heat ◽

Aerial Systems ◽

Airborne Sensors

Traditional configurations for mounting Temperature–Humidity (TH) sensors on multirotor Unmanned Aerial Systems (UASs) often suffer from insufficient radiation shielding, exposure to mixed and turbulent air from propellers, and inconsistent aspiration while situated in the wake of the UAS. Descent profiles using traditional methods are unreliable (when compared to an ascent profile) due to the turbulent mixing of air by the UAS while descending into that flow field. Consequently, atmospheric boundary layer profiles that rely on such configurations are bias-prone and unreliable in certain flight patterns (such as descent). This article describes and evaluates a novel sensor housing designed to shield airborne sensors from artificial heat sources and artificial wet-bulbing while pulling air from outside the rotor wash influence. The housing is mounted above the propellers to exploit the rotor-induced pressure deficits that passively induce a high-speed laminar airflow to aspirate the sensor consistently. Our design is modular, accommodates a variety of other sensors, and would be compatible with a wide range of commercially available multirotors. Extensive flight tests conducted at altitudes up to 500 m Above Ground Level (AGL) show that the housing facilitates reliable measurements of the boundary layer phenomena and is invariant in orientation to the ambient wind, even at high vertical/horizontal speeds (up to 5 m/s) for the UAS. A low standard deviation of errors shows a good agreement between the ascent and descent profiles and proves our unique design is reliable for various UAS missions.

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Application of small unamanned aerial systems in logistics and planning

Sustainable Forestry: Collection ◽

10.5937/sustfor1979149q ◽

2019 ◽

pp. 149-163

Author(s):

Nenad Šurjanac ◽

Natalija Momirović ◽

Marija Milosavljević ◽

Sonja Braunović ◽

Milan Kabiljo

Keyword(s):

Decision Making ◽

Field Work ◽

Relevant Information ◽

Digital Data ◽

Vegetation Coverage ◽

Unmanned Aerial Systems ◽

Large Area ◽

Computer Data ◽

Digital Formats ◽

Aerial Systems

The application of modern technologies makes it easy to collect, process, present, and apply data for logistics in hard to reach areas. Proper delivery of equipment, personnel, and materials directly affects the quality of work. The need for precise and real information about the condition of the terrain and the conditions of the environment has always existed since this knowledge enables proper planning, forecasting and task performing in the field. Improvement in the digital industry enables fast and easy transfer of unchanged digital data from the field to the information processing centers, which consequently improves decision making and planning processes. New workflows made proper logistics even more important because it increased the precision of field work and better anticipation of previously unforeseen circumstances. Work on hard to reach areas, with large slopes, non-existent and/or non-persistent infrastructure, and different degree of vegetation coverage requires precise planning and organization of works, in order to minimize the number of unforeseen situations and make the most expeditious workflows. This paper presents the practical application of small unmanned aerial systems for collecting a large amount of data in a short time, the processing of the data, and the production of relevant information for decision making. There are two most important aspects of this paper. First one is fast, easy, safe and precise collection of large amounts of data which is an alternative to the traditional methods. The second is computer data processing, which enables a fast and automatic transformation of raw data into relevant information in digital formats that are suitable for further processing and easily accessible to decision makers. This work shows that it is possible to record quickly and in detail a large area, and obtain real, current, accurate and high-fidelity information about each point of terrain, with high precision and reliability

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Quality Assessment of Photogrammetric Methods—A Workflow for Reproducible UAS Orthomosaics

Remote Sensing ◽

10.3390/rs12223831 ◽

2020 ◽

Vol 12 (22) ◽

pp. 3831

Author(s):

Marvin Ludwig ◽

Christian M. Runge ◽

Nicolas Friess ◽

Tiziana L. Koch ◽

Sebastian Richter ◽

...

Keyword(s):

Optical Sensors ◽

Spatial Data ◽

Forest Canopy ◽

Cost Effective ◽

Temporal Analysis ◽

Unmanned Aerial Systems ◽

Wide Range ◽

Very High Spatial Resolution ◽

Multi Temporal ◽

Aerial Systems

Unmanned aerial systems (UAS) are cost-effective, flexible and offer a wide range of applications. If equipped with optical sensors, orthophotos with very high spatial resolution can be retrieved using photogrammetric processing. The use of these images in multi-temporal analysis and the combination with spatial data imposes high demands on their spatial accuracy. This georeferencing accuracy of UAS orthomosaics is generally expressed as the checkpoint error. However, the checkpoint error alone gives no information about the reproducibility of the photogrammetrical compilation of orthomosaics. This study optimizes the geolocation of UAS orthomosaics time series and evaluates their reproducibility. A correlation analysis of repeatedly computed orthomosaics with identical parameters revealed a reproducibility of 99% in a grassland and 75% in a forest area. Between time steps, the corresponding positional errors of digitized objects lie between 0.07 m in the grassland and 0.3 m in the forest canopy. The novel methods were integrated into a processing workflow to enhance the traceability and increase the quality of UAS remote sensing.

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R2U2: Tool Overview

10.29007/5pch ◽

2018 ◽

Cited By ~ 1

Author(s):

Kristin Yvonne Rozier ◽

Johann Schumann

Keyword(s):

Health Management ◽

Autonomous Systems ◽

Building Blocks ◽

Unmanned Aerial Systems ◽

Critical System ◽

Safety Critical System ◽

Target Architecture ◽

Wide Range ◽

Aerial Systems ◽

Temporal Formula

R2U2 (Realizable, Responsive, Unobtrusive Unit) is an extensible framework for runtime System Health Management (SHM) of cyber-physical systems. R2U2 can be run in hardware (e.g., FPGAs), or software; can monitor hardware, software, or a combination of the two; and can analyze a range of different types of system requirements during runtime. An R2U2 requirement is specified utilizing a hierarchical combination of building blocks: temporal formula runtime observers (in LTL or MTL), Bayesian networks, sensor filters, and Boolean testers. Importantly, the framework is extensible; it is designed to enable definitions of new building blocks in combination with the core structure. Originally deployed on Unmanned Aerial Systems (UAS), R2U2 is designed to run on a wide range of embedded platforms, from autonomous systems like rovers, satellites, and robots, to human-assistive ground systems and cockpits.R2U2 is named after the requirements it satisfies; while the exact requirements vary by platform and mission, the ability to formally reason about Realizability, Responsiveness, and Unobtrusiveness is necessary for flight certifiability, safety-critical system assurance, and achievement of technology readiness levels for target systems. Realizability ensures that R2U2 is sufficiently expressive to encapsulate meaningful runtime requirements while maintaining adaptability to run on different platforms, transition be- tween different mission stages, and update quickly between missions. Responsiveness entails continuously monitoring the system under test, real-time reasoning, reporting intermediate status, and as-early-as-possible requirements evaluations. Unobtrusiveness ensures compliance with the crucial properties of the target architecture: functionality, certifiability, timing, tolerances, cost, or other constraints.

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SOME APPROACHES TO COMPERATIVE ASSESSMENT AND SELECTION OF UNMANNED AERIAL SYSTEMS

Aviation ◽

10.3846/16487788.2013.805862 ◽

2013 ◽

Vol 17 (2) ◽

pp. 57-64

Author(s):

Mykola Kulyk ◽

Valeriy Silkov ◽

Alexei Samkov

Keyword(s):

Decision Making ◽

System Application ◽

Comparative Assessment ◽

Unmanned Aerial Systems ◽

Unmanned Aerial System ◽

Distribution Of Resources ◽

Aerial Systems ◽

Selection Of

Methods to solve the problems of the comparative assessment and selection of unmanned aerial systems are offered. These methods are based on the particular indicators that display the efficiency of unmanned aerial system application. An algorithm that helps to solve such problems has been developed to create a system of support and decision making and to optimise the distribution of resources.

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Design and Development Autonomous Unmanned Aerial Vehicle Software

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.d9147.049420 ◽

2020 ◽

Vol 9 (4) ◽

pp. 2105-2108

Keyword(s):

Autonomous Navigation ◽

Application Programming Interface ◽

Detection Algorithm ◽

Mission Planning ◽

Unmanned Aerial Systems ◽

Localization And Mapping ◽

Wide Range ◽

Human Operators ◽

Emergency Scenarios ◽

Aerial Systems

Unmanned aerial vehicles are the cutting edge technology which is used in various arduous applications and emergency scenarios. But human operators find it burdensome and experience a lot of physical and mental stress while operating the aerial systems in critical and emergency scenarios such as rescue operations, mine inspection, and surveillance. Our proposed idea is to provide the autonomous capability and features to these automatons by developing a mission-planning application that can autonomously guide UAV operations even in GPS denied environments by implementing SLAM (Simultaneous Localization and Mapping). With autonomous capability, aerial systems can help to plummet the stress on human operators or may even perform the process or mission efficiently without human intervention in numerous applications. Applications involving autonomous unmanned aerial systems have increased in recent times and are being applied in a wide range of fields such as infrastructure, transport, agriculture, mining, media, and transport. This paper covers the working of the autonomous navigation algorithm, artificially intelligent object detection algorithm and the mission planning API (Application Programming Interface).

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Risk Modeling of Sequential Decision-making in the National Airspace System and with Unmanned Aerial Systems

10.18130/v3mq04 ◽

2012 ◽

Author(s):

Jin Hi Werner

Keyword(s):

Decision Making ◽

Sequential Decision Making ◽

Unmanned Aerial Systems ◽

Risk Modeling ◽

Sequential Decision ◽

National Airspace System ◽

Aerial Systems

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Urban Unmanned Aerial Systems Operations

Law in Context. A Socio-legal Journal ◽

10.26826/law-in-context.v36i2.114 ◽

2020 ◽

Vol 36 (2) ◽

pp. 1-12 ◽

Cited By ~ 1

Author(s):

Eleonora Bassi

Keyword(s):

The United States ◽

Daily Basis ◽

Economic Benefits ◽

Point Of View ◽

Unmanned Aerial Systems ◽

The European Union ◽

The United Kingdom ◽

Wide Range ◽

Delivery Services ◽

Aerial Systems

The drone sector offers a wide range of affordances, opportunities, and economic benefits for society. Delivery services, agriculture monitoring, wildfire control, public infrastructure inspections, humanitarian aid, or drone journalism, are among the activities enhanced by unmanned aerial systems (UAS). No surprise the civilian UAS market is growing fast throughout the world. Yet, on a daily basis, newspapers report serious concerns for people infringing other people’s rights through the use of drones. Cybersecurity attacks, data theft, criminal offences brought about the use of this technology frame the picture. Nowadays, several countries are changing their legal rules to properly address such challenges. In 2018, the European Union (EU) started its five year-long regulative process that should establish the common rules and standards for UAS operations within the EU Single Sky by 2023. A similar timeline has been adopted in the United States, so as to provide the jurisdictional boundaries for the civilian use of drones. The United Kingdom (UK) and Japan are adopting new rules too. From a legal point of view, the overall framework is thus rapidly evolving. The aim of this paper is to give attention to (i) privacy and data protection concerns raised by UAS operations; (ii) their monitoring functions and corresponding surveillance issues; and, (iii) how a privacy preserving approach – such as with privacy by design technologies, organizational measures, audit procedures, civic involvement, to name a few – makes a lawful and ethical use of this powerful technology possible.

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Evaluating the Use of Unmanned Aerial Systems (UAS) to Perform Low-Slope Roof Inspections

10.29007/jknh ◽

2020 ◽

Author(s):

Dr. Dhaval Gajjar ◽

Dr. Joseph Burgett

Keyword(s):

3D Model ◽

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Inspection Time ◽

Unmanned Aerial Systems ◽

Traditional Practices ◽

Aircraft Systems ◽

Federal Highway ◽

Wide Range ◽

Aerial Systems

The use of Unmanned Aircraft Systems (UAS) or Drones are being explored for a wide range of civilian applications. The Federal Highway Administration (FHWA) recently reported that “construction inspectors that use UAS are reducing inspection time, improving effectiveness, increasing safety, and lowering costs.” If the FHWA is enjoying these benefits by leveraging this technology, it stands to reason that other industries that perform similar functions would also benefit. This study explores the opportunity of using commercially available UAS and structure-from-motion software to replace an in-person inspection for a low slope roof. The goal of the study was to see how much of a traditional in-person roof inspection could be replaced with a 3D photogrammetric model created from drone imagery. In this experiment, a SME roofing inspector identified deficiencies exclusively from a 3D model. Then, the SME inspected the low-slope roof in-person using traditional practices. The SME identified 191 specific deficiencies using 3D model and 200 deficiencies from the traditional method. The defects easiest to identify were open laps, alligatoring, punctures, wrinkles on the roof membrane and damages around the edges whereas total number and square feet of blisters, damages around penetration were the most difficult to identify in the model.

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Effect of Sensor Sensitivity on Autonomous Aerial Vehicle Target Localization

Unmanned Systems ◽

10.1142/s2301385021500023 ◽

2020 ◽

Vol 09 (01) ◽

pp. 11-21

Author(s):

Nate Quirion ◽

Dahai Liu

Keyword(s):

Decision Making ◽

Intelligent Systems ◽

Research Direction ◽

Target Localization ◽

Hierarchical Architecture ◽

Future Research ◽

Unmanned Aerial Systems ◽

Test Bed ◽

Sensor Sensitivity ◽

Aerial Systems

In recent years, Unmanned Aerial Systems (UASs) development and application have achieved remarkable growth. With the advancement of technology, UASs nowadays feature more advanced autonomous capabilities than ever before. In order to achieve autonomous behavior, intelligent systems are required to be incorporated to support system learning, control and decision-making. With these capabilities, UASs can learn from their past experiences, through interacting with the task environment to adapt their behavior to enhance their future performance. Machine learning is one of the most commonly used techniques for UASs to acquire knowledge from their experience, and research in this area is still developing. In this study, Reinforcement Learning (RL) algorithms were used on autonomous aerial systems to achieve adaptive behavior and decision-making capabilities. The effects of UAS sensor sensitivity, as modeled through Signal Detection Theory (SDT), on the ability of RL algorithms to accomplish a target localization task were investigated. Three levels of sensor sensitivity were simulated and compared to the results of the same system using a perfect sensor, with the consideration of two RL algorithms, namely, Temporal Difference (TD) and Monte Carlo (MC) methods. Target localization and identification task were used as the test bed, and a hierarchical architecture was developed with two distinct agents. Mission performance was analyzed using multiple metrics, including episodic reward and the time taken to locate all targets. Statistical analyses were carried out to detect significant differences in the comparison of steady-state behavior of different factors. Results were discussed, and future research direction was given at the end of the paper.

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